A total of 100 blood samples taken from patients with suspected typhoid fever aged between (1-60) years, were involved in this study. Blood samples were cultured directly on brain heart infusion broth. After that sub cultured of isolates on MacConkey agar and XLD agar and S.S agar to find the Salmonella typhi then identified by the biochemical and antibiotic sensitivity test. Resistant genes were identified by using aacc2 gene and cat gene. Results showed that there was 7 Salmonella typhi isolates from blood culture, as well as, aacc2 gene success in amplification of 450bp fragment for amino glycoside resistant, while not improve amplification

A total of 551 water samples (drinking and raw water) were collected In this study, Aeromonas.hydrophila, were detected by biochemical tests and PCR (16s rRNA gene). The results of identification showed that A.hydrophila had recovery rate 63 isolates (49.21%). The results revealed that all A.hydrophila isolates were PCR positive or the 16S rRNA gene and the results of sequencing showed that two isolates of A.hydrophila(local isolates) had percentage similarities 100% with A. hydrophila ATCC 7966 in GenBank database .All strains had a minimal Inhibitory Concentration(MIC) distribution pattern for lead cetate rranged (900-1200 μg/ml), and mercury chloride ranged (40-80 μg /ml).

The antimicrobial potency of the crude ethanolic extracts from different Iraqi plants were evaluated . Further more, total sesquiterpene lactones and phenolic compounds were isolated and their antimicrobial activity attempted. The results indicated that crude extracts have no activity except that of Callistemon lanceolatus. Also, the sesquiterpene lactones and phenolic compounds isolated from Callistemon lanceolatus were the most significant antimicrobial active constituents of the studied plants.

This study is aimed to Green-synthesize and characterize Al NPs from Clove (Syzygium aromaticum
L.) buds plant extract and to investigate their effect on isolated and characterized Salmonella enterica growth.
S. aromaticum buds aqueous extract was prepared from local market clove, then mixed with Aluminum nitrate
Al(NO3)3. 9 H2O, 99.9% in ¼ ratio for green-synthesizing of Al NPs. Color change was a primary confirmation
of Al NPs biosynthesis. The biosynthesized nanoparticles were identified and characterized by AFM, SEM,
EDX and UV–Visible spectrophotometer. AFM data recorded 122nm particles size and the surface roughness
RMs) of the pure S. aromaticum buds aqueous extract recorded 17.5nm particles s

IA Ali, FK Emran, DF Salloom, Annals of the Romanian Society for Cell Biology, 2021

Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho

Diabetic retinopathy is an eye disease, because of pressure in eye nerve fiber. It is a major cause of blindness in middle as well as older age groups; therefore it is essential to diagnose it earlier. Some of the challenges are in the diagnosis of the disease is detection edges of the image, may be some important edges are missed outcome the noise around the corners.
Wherefore, in order to reduce these effects in this paper, we proposed a new technique for edge detection using traditional operators in combination with fuzzy logic based on fuzzy inference system. The results show that the proposed fuzzy edge detection technique better than of traditional techniques, where vascular are markedly detected over the original.

Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

The Normalization Difference Vegetation Index (NDVI), for many years, was widely used in remote sensing for the detection of vegetation land cover. This index uses red channel radiances (i.e., 0.66 μm reflectance) and near-IR channel (i.e., 0.86 μm reflectance). In the heavy chlorophyll absorption area, the red channel is located, while in the high reflectance plateau of vegetation canopies, the Near-IR channel is situated. Senses of channels (Red & Near- IR) read variance depths over vegetation canopies. In the present study, a further index for vegetation identification is proposed. The normalized difference vegetation shortwave index (NDVSI) is defined as the difference between the cubic bands of Near- IR and Shortwave infrared